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Ecological Informatics is defined as an interdisciplinary framework promoting the use of advanced computational technology for elucidating the principles of information processing at and between all levels of complexity of ecosystems - from genes to ecological networks (see http://www.waite.adelaide.edu.au/ISEI/). Since the first meeting in Toulouse, France in 1998, various computational methods have been demonstrated in ecological information processing, data management (archival, retrieval and visualization), ecosystems study (systems analysis, synthesis and forecasting), and ecosystem decision support. Biologically -inspired computation techniques, such as artificial neural networks, fuzzy logic, cellular automata, genetic/evolutionary algorithms, support vector machines, and adaptive agents, have been considered as core techniques in ecological informatics. At the 4th meeting in Busan (Pusan), we are going to focus on advanced interpretation of ecosystems exposed to various natural and anthropogenic stresses by utilizing the state-of-art computational methods. Attention will especially be given to how the developed computational methods could be efficiently applied a wider spectrum of real situations across different scales from genes to ecosystems and how generalities in information processing could be explored in different biological units. Additionally, we would like to concentrate on educating the universality of ecological measures in expressing ecosystems exposed to various sources of natural and anthropogenic stresses. By objective quantification of ecosystem characters, we will take a close look at how ecosystems could be objectively compared across different regimes: different geographic areas (e.g. nations, continents), different pollution strengths and agents, different taxa, and different fields (e.g. fishery, agriculture, conservation, etc). The conference will cover the following topics and relevant subjects:
o Molecules and physiology o Behavior o Population o Community o Ecosystem
o Forecasting, conservation/management strategies and policies o Aquatic ecosystems (e.g., river/stream, lake, estuary, marine system, etc.) o Terrestrial ecosystems (e.g., forest, soil, urban and suburban area, etc.) o Applied ecology: fishery, forestry, agriculture, epidemic/endemic, etc. o Ecosystem health, ecosystem quality estimation, water quality assessment, etc o Ecosystem theory and methodology o Remote sensing and landscape ecology o Image
processing and pattern recognition
o Artificial neural networks o Fuzzy logic o Cellular automata o Evolutionary/Genetic algorithms o Support Vector machines o Adaptive agents o Network analysis o Information processing based on neural systems o Other biologically-and physically-inspired data processing and computational methods |
Scope